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Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, Global Edition eBook, 11th Edition

Ramesh Sharda
...show all

Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, Global Edition eBook, 11th Edition

By Ramesh Sharda, Dursun Delen, Efraim Turban
$65.00
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Overview
Author
Ramesh Sharda
...show all
Edition
11th
ISBN
9781292341606
Published Date
04/03/2020
For courses in decision support systems, computerized decision-making tools, and management support systems.

Market-leading guide to modern analytics, for better business decisions

Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus — analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.

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Features
  • A new focus on analytics and its enabling technologies
  • Motivations, concepts, methods, and methodologies for different types of analytics (focusing heavily on predictive and prescriptive analytics)
  • New technology trends as the enablers of modern-day analytics such as AI, machine learning, deep learning, robotics, IoT, and smart/robo-collaborative assisting systems.
  • The authors have streamlined coverage to optimise the text’s size and content. This includes adding material on cutting-edge analytics, AI trends, and technologies, while eliminating older, less-used material.
  • A 100% new Chapter 2, “Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications,” covers AI essentials and examples illustrating the benefits of AI to businesses across industries.
  • A 90% new Chapter 6, “Deep Learning and Cognitive Computing,” covers machine learning, deep learning, and the increasingly popular AI topic cognitive computing.
  • A 100% new Chapter 10, “Robotics: Industrial and Consumer Applications,” introduces robotics applications in industry and for consumers, as well as the impact of such advances on jobs, plus legal ramifications.
  • A 95% new Chapter 12, “Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors,” concentrates on these knowledge systems and their implications.
  • A 100% new Chapter 13, “The Internet of Things As A Platform For Intelligent Applications,” introduces IoT as an enabler of analytics and AI applications. Topics include smart homes, smart cities, and autonomous vehicles.
  • An 85% new Chapter 14, “Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts,” deals with implementation issues of intelligent systems, including analytics.
  • Several chapters have new opening vignettes that are based on recent stories and events.
  • Application cases throughout the text are new or have been updated to include recent examples of applications of a specific technique/model. Discussion questions are included.
  • Most chapters have new exercises, Internet assignments, and discussion questions throughout.
New to this edition
  • The text is now organised around two main themes:
    • Motivations, concepts, methods, and methodologies for different types of analytics (focusing heavily on predictive and prescriptive analytics), and
    • New technology trends as the enablers of modern-day analytics such as AI, machine learning, deep learning, robotics, IoT, and smart/robo-collaborative assisting systems.
  • The authors have streamlined coverage to optimise the text’s size and content. This includes adding material on cutting-edge analytics, AI trends, and technologies, while eliminating older, less-used material.
  • A 100% new Chapter 2, “Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications,” covers AI essentials and examples illustrating the benefits of AI to businesses across industries.
  • A 90% new Chapter 6, “Deep Learning and Cognitive Computing,” covers machine learning, deep learning, and the increasingly popular AI topic cognitive computing.
  • A 100% new Chapter 10, “Robotics: Industrial and Consumer Applications,” introduces robotics applications in industry and for consumers, as well as the impact of such advances on jobs, plus legal ramifications.
  • A 95% new Chapter 12, “Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors,” concentrates on these knowledge systems and their implications.
  • A 100% new Chapter 13, “The Internet of Things As A Platform For Intelligent Applications,” introduces IoT as an enabler of analytics and AI applications. Topics include smart homes, smart cities, and autonomous vehicles.
  • An 85% new Chapter 14, “Implementation Issues: From Ethics and Privacy to Organisational and Societal Impacts,” deals with implementation issues of intelligent systems, including analytics.
  • Several chapters have new opening vignettes that are based on recent stories and events.
  • Application cases throughout the text are new or have been updated to include recent examples of applications of a specific technique/model. Discussion questions are included.
  • Most chapters have new exercises, Internet assignments, and discussion questions throughout.
Table of contents
  • PART I: INTRODUCTION TO ANALYTICS AND AI
  • 1. An Overview of Business Analytics, Decision Support Systems, Business Intelligence, Data Science, and Artificial Intelligence
  • 2. Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications
  • 3. Nature of Data, Statistical Modeling, and Visualization
  • PART II: PREDICTIVE ANALYTICS AND MACHINE LEARNING
  • 4. Data Mining Process, Methods, and Applications
  • 5. Machine learning Techniques for Predictive Analytics
  • 6. Deep Learning and Cognitive Computing
  • 7. Text Mining, Sentiment Analysis, and Social Analytics
  • PART III: PRESCRIPTIVE ANALYTICS AND BIG DATA
  • 8. Prescriptive Analytics with Optimization and Simulation
  • 9. Big Data, Location Analytics, and Cloud Computing
  • PART IV: ROBOTICS, SOCIAL NETWORKS, AI, AND IoT
  • 10. Robotics: Industrial and Consumer Applications
  • 11. Group Decision Making, Collaborative Systems, and AI Support
  • 12. Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors
  • 13. The Internet of Things As a Platform for Intelligent Applications
  • PART V: CAVEATS OF ANALYTICS AND AI
  • 14. Implementation Issues: From Ethics and Privacy to Organizational and Societal Impacts